Tourism investment project risk assessment method and early warning system

Abstract

The invention discloses a tourism investment project risk assessment method and early warning system, and the method comprises the steps: S1, determining tourism investment project risk assessment indexes which comprise external risks, investment subject internal risks and project engineering risks; s2, based on the Bayesian theorem, constructing a risk assessment model used for calculating the occurrence probability of each risk index and the influence on the overall risk of the project, defining a prior probability for each risk index according to historical data or expert experience, continuously collecting latest data related to the risk assessment indexes, and according to the newly collected data, establishing a risk assessment model; using a Bayesian algorithm to update the posterior probability of each risk index; s3, comprehensively evaluating the posterior probability of each risk index, and calculating the overall risk level of the project; according to the method, the external risk, the internal risk of the investment subject and the project engineering risk are covered by defining the risk assessment indexes, and the comprehensive coverage of the risk points is ensured, so that the problem of incomplete risk assessment caused by missing important risk points can be reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of tourism construction, and particularly to a risk assessment method and early warning system for tourism investment projects. Background Art

[0002] With the advancement of globalization and economic integration, the tourism industry, as an important part of the service industry, has developed rapidly. Tourism investment projects have emerged continuously, providing investors with rich investment options and opportunities. Tourism investment projects usually have characteristics such as long-term and uncertainty. These characteristics make investors face many risks when making tourism investments. Such as external risks, risks of the investment entity itself, and project engineering risks, etc., which may have a significant impact on the growth space and operation mode of the tourism industry.

[0003] In the prior art, it is difficult to comprehensively evaluate external risks, risks of the investment entity itself, and project engineering risks, and important risk points may be omitted, resulting in incomplete and inaccurate risk assessment. Therefore, a risk assessment method and early warning system for tourism investment projects are proposed. Summary of the Invention

[0004] The purpose of the present invention is to solve the disadvantages in the prior art that it is difficult to comprehensively evaluate external risks, risks of the investment entity itself, and project engineering risks, and important risk points may be omitted, resulting in incomplete and inaccurate risk assessment, and to propose a risk assessment method and early warning system for tourism investment projects.

[0005] To achieve the above purpose, the present invention adopts the following technical solutions:

[0006] A risk assessment method for tourism investment projects, including:

[0007] S1: Define risk assessment indicators for tourism investment projects. The risk assessment indicators include external risks, internal risks of the investment entity, and project engineering risks;

[0008] S2: Build a risk assessment model based on Bayes' theorem for calculating the occurrence probability of each risk indicator and its impact on the overall project risk. Define prior probabilities for each risk indicator according to historical data or expert experience, continuously collect the latest data related to the risk assessment indicators, and update the posterior probabilities of each risk indicator using the Bayes algorithm according to the newly collected data;

[0009] S3: Comprehensively evaluate the posterior probabilities of each risk indicator and calculate the overall project risk level;

[0010] S4: Set risk levels including extreme risk, severe risk, moderate risk, and mild risk, compare the calculated overall project risk level with the set risk levels, and determine the current project risk level;

[0011] S5: When the project risk level reaches or exceeds the set warning threshold, trigger the risk warning mechanism and formulate a risk response strategy according to the risk level.

[0012] The above technical solution further includes:

[0013] Preferably, in S1, the external risks include policy risks, market risks, and tourist consumption demand risks; the internal risks of the investment entity include income target risks, funding source risks, and management level risks; the project engineering risks include engineering environment risks, construction technology risks, construction duration risks, and material cost risks.

[0014] Preferably, the specific steps for constructing a risk assessment model based on Bayes' theorem to calculate the occurrence probability of each risk indicator and its impact on the overall project risk are as follows:

[0015] Determine risk indicators and prior probabilities: Identify risk indicators including external risks, internal risks of the investment entity, and project engineering risks, and based on historical data or expert experience, for each risk indicator A i Define the prior probability P(A i );

[0016] Construct a Bayes model: For each risk indicator A i , assuming that the conditional probability of observing new data B given the occurrence of this risk indicator is P(B|A i ), use Bayes' theorem to calculate the posterior probability where P(B) is the total probability of the observed new data B, calculated by the total probability formula: P(B) = ∑ i P(B|A i ) · P(A i );

[0017] Comprehensively evaluate and calculate the overall risk: For each risk indicator A i use Bayes' theorem to calculate the posterior probability P(A i |B), and based on the posterior probabilities of each risk indicator, combined with the risk indicator weights, calculate the overall project risk level and output the calculation result.

[0018] Preferably, the specific steps for defining the prior probability for each risk indicator according to historical data or expert experience are as follows:

[0019] Collect historical data: Identify and determine the sources of historical data related to the risk assessment of tourism investment projects, such as past project records, industry reports, expert experience, etc. Organize the collected historical data, remove duplicate, incorrect, or incomplete data to ensure the accuracy and consistency of the data;

[0020] Calculate the prior probability: For risk indicators with historical records, use the frequency estimation method to calculate the prior probability. For the policy change risk among external risks, count the frequency of past policy changes and calculate its prior probability P(A i ): where A1 represents the event of the occurrence of the policy change risk. For risk indicators lacking historical records, invite experts to score and evaluate. Experts, based on their professional knowledge and experience, score the occurrence possibility of each risk indicator and calculate the prior probability accordingly. And use an independent historical data set or expert opinion to verify the calculated prior probability. If the verification result shows that the prior probability is deviated or unreasonable, make necessary adjustments according to the verification result.

[0021] Preferably, the specific process of comprehensively evaluating the posterior probabilities of each risk indicator and calculating the overall project risk level is as follows:

[0022] Determine the risk indicator weights: Invite experts to score the importance of each risk indicator. Experts with relevant experience and professional knowledge determine the weight ω of each risk indicator according to the expert opinion i , and the sum of the weights of all risk indicators is 1, that is

[0023] Obtain the posterior probability P(A i |B) of each risk indicator from the Bayesian algorithm, where A i represents the i-th risk indicator event, B represents the newly collected data, and use the weight ω i and the posterior probability P(A i |B) to calculate the weighted posterior probability P′(A i |B): P′(A i |B) = ω i ·P(A i |B);

[0024] Calculate the risk index: Add up the weighted posterior probabilities of all risk indicators to obtain the overall project risk index R: The risk index R reflects the level of the overall project risk.

[0025] Preferably, the specific steps for setting risk levels including extreme risk, severe risk, moderate risk, and mild risk are as follows:

[0026] Set the extreme risk threshold as R 极度 , the severe risk threshold as R 重度 , the moderate risk threshold as R 中度 , then the risk level division is expressed as: Extreme risk: R > R 极度 , Severe risk: R 重度≤R<R 极度 , Medium risk: R 中度 ≤R<R 重度 , Low risk: R < R 中度 , Extreme risk indicates that the project faces extremely high risks, which may lead to project failure or serious losses; High risk means the project faces relatively high risks and requires close attention and measures; Medium risk means the project faces certain risks but is still within the controllable range; Low risk means the project has relatively low risks and basically will not affect the project progress.

[0027] Preferably, formulating risk response strategies according to risk levels specifically includes:

[0028] Extreme risk response strategy: Immediately stop or adjust the project, seek external support, and formulate an emergency plan;

[0029] High risk response strategy: Strengthen risk monitoring, optimize the risk management process, and take risk reduction measures;

[0030] Medium risk response strategy: Continuously monitor risk changes, formulate a risk mitigation plan, and strengthen internal communication;

[0031] Low risk response strategy: Conduct regular risk management, enhance risk awareness, and review risks regularly.

[0032] Preferably, the risk early warning system for tourism investment projects corresponding to the risk assessment method for tourism investment projects includes:

[0033] Risk index definition and data collection module: Responsible for defining the risk assessment indicators of tourism investment projects, including external risks, internal risks of investment entities, and project engineering risks, and collecting data related to risk indicators;

[0034] Bayesian risk assessment model module: Responsible for constructing a risk assessment model based on Bayes' theorem, calculating the occurrence probabilities of each risk indicator, and evaluating its impact on the overall project risk;

[0035] Overall project risk assessment module: Responsible for comprehensively evaluating the posterior probabilities of each risk indicator and calculating the overall project risk level;

[0036] Risk level comparison and decision-making module: Responsible for comparing the calculated overall project risk level with the preset risk level threshold to determine the current project risk level;

[0037] Risk early warning and response mechanism module: Responsible for triggering the corresponding risk early warning mechanism when the project risk level reaches or exceeds the set warning threshold, and formulating corresponding response strategies according to different risk levels.

[0038] The present invention has the following beneficial effects:

[0039] 1. In the present invention, by defining risk assessment indicators, this method covers external risks, internal risks of the investment entity, and project engineering risks, ensuring comprehensive coverage of risk points, which helps to reduce the problem of incomplete risk assessment caused by missing important risk points.

[0040] 2. In the present invention, the risk assessment model constructed based on Bayes' theorem can continuously collect the latest data related to risk assessment indicators and update the posterior probabilities of each risk indicator according to the new data. This dynamic update mechanism improves the accuracy and timeliness of risk assessment. By comprehensively evaluating the posterior probabilities of each risk indicator, this method can calculate the overall risk level of the project, which helps investors and managers more intuitively understand the overall risk situation of the project. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 is a flowchart of the risk assessment method for tourism investment projects proposed by the present invention;

[0042] Figure 2 is a system architecture diagram of the risk early warning system for tourism investment projects proposed by the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0043] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0044] As Figure 1 shown, the risk assessment method for tourism investment projects includes:

[0045] S1: Define the risk assessment indicators for tourism investment projects. The risk assessment indicators include external risks, internal risks of the investment entity, and project engineering risks;

[0046] S2: Construct a risk assessment model based on Bayes' theorem for calculating the occurrence probability of each risk indicator and its impact on the overall project risk. Define the prior probabilities for each risk indicator according to historical data or expert experience, continuously collect the latest data related to the risk assessment indicators, and update the posterior probabilities of each risk indicator using the Bayes algorithm according to the newly collected data;

[0047] S3: Comprehensively evaluate the posterior probabilities of each risk indicator and calculate the overall risk level of the project;

[0048] S4: Set risk levels including extreme risk, high risk, medium risk, and low risk. Compare the calculated overall project risk level with the set risk levels to determine the current project risk level.

[0049] S5: When the project risk level reaches or exceeds the set warning threshold, trigger the risk warning mechanism and formulate a risk response strategy based on the risk level.

[0050] In the embodiments of the present invention, through the risk assessment model constructed based on Bayes' theorem, this method can dynamically update the occurrence probabilities of each risk indicator. Using the prior probabilities defined by historical data or expert experience as a starting point, as new data is collected, the posterior probabilities are continuously corrected using the Bayes' algorithm, making the risk assessment more accurate and timely. By comprehensively evaluating the posterior probabilities of each risk indicator, the overall risk level of the project can be calculated. At the same time, by setting clear risk levels (such as extreme risk, high risk, medium risk, low risk), the current risk status of the project can be intuitively understood, facilitating decision-makers to make quick and accurate responses.

[0051] In one embodiment, the external risks in S1 include policy risk, market risk, and tourist consumption demand risk; the internal risks of the investment entity include revenue target risk, funding source risk, and management level risk; and the project engineering risks include engineering environment risk, construction technology risk, construction duration risk, and material cost risk.

[0052] In the embodiments of the present invention, policy risk represents the degree of impact of policy changes on the project; market risk represents the impact of market demand, competition situation, price fluctuations, etc. on the project; tourist consumption demand risk represents the impact of tourist preferences and consumption trend changes on the project; revenue target risk represents whether the revenue target set by the investment entity is reasonable and the possibility of its achievement; funding source risk represents the stability of the funding source and the sufficiency of the amount; management level risk represents the management ability and decision-making efficiency of the investment entity; engineering environment risk represents the impact of natural conditions such as construction geology and climate; construction technology risk represents the maturity and reliability of construction technology; construction duration risk represents the control of project progress and delay risk; and material cost risk represents the impact of material price fluctuations on the project cost.

[0053] In one embodiment, the specific steps for constructing a risk assessment model based on Bayes' theorem to calculate the occurrence probabilities of each risk indicator and its impact on the overall project risk are as follows:

[0054] Determine risk indicators and prior probabilities: Identify risk indicators including external risks, internal risks of the investment entity, and project engineering risks, and based on historical data or expert experience, for each risk indicator A i Define the prior probability P(A i )

[0055] Construct a Bayesian model: For each risk indicator A i , assuming that given the occurrence of this risk indicator, the conditional probability of observing new data B is P(B|A i ), use Bayes' theorem to calculate the posterior probability P(A i |B): where P(B) is the total probability of the observed new data B, calculated by the law of total probability: P(B) = ∑ i P(B|A i )·P(A i );

[0056] Comprehensive evaluation and calculation of the overall risk: For each risk indicator A i Use Bayes' theorem to calculate the posterior probability P(A i |B). According to the posterior probabilities of each risk indicator, combined with the risk indicator weights, calculate the overall risk level of the project, and output the calculation results.

[0057] In an embodiment of the present invention, it is assumed that in a real estate construction project, three risk indicators are defined: external risk (market volatility): the prior probability is 0.3, indicating that the occurrence probability of market volatility is 30%, investment subject risk (fund shortage): the prior probability is 0.2, indicating that the occurrence probability of fund shortage is 20%, engineering risk (construction delay): the prior probability is 0.5, indicating that the occurrence probability of construction delay is 50%. It is assumed that during the project progress, the latest data B from the market is received, and the occurrence probability of the external risk (market volatility) is updated according to the latest data. Through Bayes' formula, the updated posterior probability is calculated. After the posterior probabilities of each risk indicator are calculated, they are combined with their respective weights to calculate the overall risk of the project. It is assumed that the weights of each risk indicator are: the external risk weight is 0.4, the investment subject risk weight is 0.3, and the engineering risk weight is 0.3. It is assumed that the updated posterior probabilities are: the external risk posterior probability is 0.35, the investment subject risk posterior probability is 0.25, and the engineering risk posterior probability is 0.45. Then the overall risk of the project is calculated by weighted average: project overall risk = (0.35×0.4) + (0.25×0.3) + (0.45×0.3) = 0.35, which indicates that the overall risk level of the project is 35%.

[0058] In one embodiment, the specific steps for defining the prior probabilities for each risk indicator according to historical data or expert experience are as follows:

[0059] Collect historical data: Identify and determine the sources of historical data related to the risk assessment of tourism investment projects, and organize the collected historical data;

[0060] Calculate the prior probability: For risk indicators with historical records, the frequency estimation method is used to calculate the prior probability. For the policy change risk among external risks, assume that the frequency of past policy changes is statistically counted, and its prior probability P(A i ) is calculated: where A1 represents the event of the occurrence of the policy change risk. For risk indicators lacking historical records, experts are invited to conduct scoring evaluations

[0061] In the embodiment of the present invention, assume that among 15 tourism projects in the past 10 years, 5 have been affected by policy changes. Then, the prior probability of policy changes is calculated by frequency estimation as follows: Therefore, the prior probability of the policy change risk is 0.33, indicating that there is a 33% probability that this tourism investment project will be affected by policy changes. Assume that historical data is insufficient to evaluate the occurrence frequency of market demand fluctuations. By inviting 3 experts to evaluate the risk of market demand fluctuations, the evaluation results of the experts are as follows: Expert 1 evaluates the probability of the occurrence of this risk as 0.4, Expert 2 evaluates the probability of the occurrence of this risk as 0.5, and Expert 3 evaluates the probability of the occurrence of this risk as 0.6. Then, the prior probability of market demand fluctuations is obtained by taking the average: Then, the prior probability of the market demand fluctuation risk is 0.5, indicating that the possibility of the occurrence of this risk is 50%.

[0062] In one embodiment, the posterior probabilities of each risk indicator are comprehensively evaluated, and the specific process of calculating the overall risk level of the project is as follows:

[0063] Determine the risk indicator weights: Invite experts to score the importance of each risk indicator, and determine the weight ω of each risk indicator according to the expert opinions i , and the sum of the weights of all risk indicators is 1, that is

[0064] Obtain the posterior probability P(A i |B) of each risk indicator from the Bayesian algorithm, where A i represents the time of the i-th risk indicator, B represents the newly collected data, and use the weight ω i and the posterior probability P(A i |B) to calculate the weighted posterior probability P′(A i |B): P′(A i |B) = ω i ·P(A i |B);

[0065] Calculate the risk index: Add up the weighted posterior probabilities of all risk indicators to obtain the overall risk index R of the project:

[0066] In one embodiment, the specific steps for setting risk levels including extreme risk, high risk, medium risk, and low risk are as follows:

[0067] Let the extreme risk threshold be R 极度 , the high risk threshold be R 重度 , the medium risk threshold be R 中度 , then the risk level division is expressed as: Extreme risk: R > R 极度 , High risk: R 重度 ≤ R < R 极度 , Medium risk: R 中度 ≤ R < R 重度 , Low risk: R < R 中度 .

[0068] In one embodiment, formulating risk response strategies according to risk levels specifically includes:

[0069] Extreme risk response strategy: Immediately stop or adjust the project, seek external support, and formulate an emergency plan;

[0070] High risk response strategy: Strengthen risk monitoring, optimize the risk management process, and take risk reduction measures;

[0071] Medium risk response strategy: Continuously monitor risk changes, formulate a risk mitigation plan, and strengthen internal communication;

[0072] Low risk response strategy: Conduct routine risk management, enhance risk awareness, and review risks regularly.

[0073] In the embodiments of the present invention, immediately stopping or adjusting the project means that in the case where the risk cannot be controlled or reduced, consideration should be given to immediately stopping the project or making major adjustments. Seeking external support means cooperating with professional risk management institutions or insurance companies to seek ways to transfer or share risks. Formulating an emergency plan means establishing an emergency response mechanism to ensure that rapid actions can be taken in case of risks and losses can be reduced. Strengthening risk monitoring means increasing the frequency and scope of risk monitoring to promptly discover and handle potential risks. Optimizing the risk management process means improving the risk management system to enhance the efficiency and accuracy of risk management. Taking risk reduction measures means reducing the likelihood and impact of risks through technological improvements, resource allocation, etc. Continuously paying attention to risk changes means maintaining attention to risks and regularly evaluating the risk level. Formulating a risk mitigation plan means formulating mitigation measures for specific risks, such as strengthening training and raising employees' safety awareness. Strengthening internal communication means ensuring that the project team has a clear understanding and unified comprehension of risks. Conventional risk management means managing and monitoring according to the established risk management process. Raising risk awareness means enhancing the project team's risk awareness through training, publicity, etc. Regularly reviewing risks means regularly reviewing and evaluating risks to ensure that the risk level remains within a controllable range.

[0074] As Figure 2 shown, the risk early warning system for tourism investment projects includes:

[0075] The risk index definition and data collection module: responsible for defining the risk assessment indicators for tourism investment projects, including external risks, internal risks of investment entities, and project engineering risks, and collecting data related to the risk indicators;

[0076] The Bayesian risk assessment model module: responsible for constructing a risk assessment model based on Bayes' theorem, calculating the occurrence probabilities of each risk indicator, and evaluating its impact on the overall project risk;

[0077] The overall project risk assessment module: responsible for comprehensively evaluating the posterior probabilities of each risk indicator and calculating the overall project risk level;

[0078] The risk level comparison and decision-making module: responsible for comparing the calculated overall project risk level with the preset risk level threshold to determine the current project risk level;

[0079] The risk early warning and response mechanism module: responsible for triggering the corresponding risk early warning mechanism when the project risk level reaches or exceeds the set warning threshold, and formulating corresponding response strategies according to different risk levels.

[0080] Although embodiments of the present invention have been shown and described, those of ordinary skill in the art will appreciate that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A risk assessment method for tourism investment projects, characterized in that, Including: S1: Define the risk assessment indicators for tourism investment projects. The risk assessment indicators include external risks, internal risks of the investment entity, and project engineering risks. S2: Construct a risk assessment model based on Bayes' theorem to calculate the occurrence probability of each risk indicator and its impact on the overall project risk. Define the prior probability for each risk indicator according to historical data or expert experience. Continuously collect the latest data related to the risk assessment indicators, and use the Bayes' algorithm to update the posterior probability of each risk indicator according to the newly collected data. S3: Comprehensively evaluate the posterior probabilities of each risk indicator and calculate the overall risk level of the project. S4: Set risk levels including extreme risk, severe risk, moderate risk, and mild risk. Compare the calculated overall risk level of the project with the set risk levels to determine the current project risk level. S5: When the project risk level reaches or exceeds the set warning threshold, trigger the risk warning mechanism and formulate risk response strategies according to the risk level.

2. The risk assessment method for tourism investment projects according to claim 1, wherein In S1, the external risks include policy risks, market risks, and tourist consumption demand risks. The internal risks of the investment entity include revenue target risks, funding source risks, and management level risks. The project engineering risks include engineering environment risks, construction technology risks, construction duration risks, and material cost risks.

3. The risk assessment method for tourism investment projects according to claim 1, wherein, The specific steps for constructing a risk assessment model based on Bayes' theorem to calculate the occurrence probability of each risk indicator and its impact on the overall project risk are as follows: Determine risk indicators and prior probabilities: Clearly define risk indicators that include external risks, internal risks of the investment entity, and project engineering risks, and based on historical data or expert experience, for each risk indicator A i Define the prior probability P(A i ); Construct a Bayesian model: For each risk indicator A i , assume that the conditional probability of observing new data B given the occurrence of this risk indicator is P(B|A i ). Use Bayes' theorem to calculate the posterior probability P(A i |B): where P(B) is the total probability of the observed new data B, calculated by the law of total probability: P(B) = ∑ i P(B|A i )·P(A i ); Comprehensive assessment and calculation of the overall risk: For each risk indicator A i Use Bayes' theorem to calculate the posterior probability P(A i |B). Based on the posterior probabilities of each risk indicator and combined with the risk indicator weights, calculate the overall risk level of the project and output the calculation results.

4. The risk assessment method for tourism investment projects according to claim 1, wherein The specific steps for defining the prior probability for each risk indicator according to historical data or expert experience are as follows: Collect historical data: Identify and determine the sources of historical data related to the risk assessment of tourism investment projects, and organize the collected historical data. Calculate the prior probability: For risk indicators with historical records, the frequency estimation method is used to calculate the prior probability. For the policy change risk among external risks, assume that the frequency of past policy changes is statistically counted to calculate its prior probability P(A i ): where A1 represents the event of the occurrence of the policy change risk. For risk indicators lacking historical records, invite experts to conduct scoring and evaluation 5. The risk assessment method for tourism investment projects according to claim 1, wherein The specific process for comprehensively evaluating the posterior probabilities of each risk indicator and calculating the overall risk level of the project is as follows: Determine the weights of risk indicators: Invite experts to score the importance of each risk indicator, and determine the weight ω of each risk indicator according to the experts' opinions i , and the sum of the weights of all risk indicators is 1, that is Obtain the posterior probability P(A i |B) of each risk indicator from the Bayesian algorithm, where A i represents the time of the i-th risk indicator, B represents the newly collected data, and use the weight ω i and the posterior probability P(A i |B) to calculate the weighted posterior probability P′(A i |B): P′(A i |B) = ω i ·P(A i |B); Calculate the risk index: Add the weighted posterior probabilities of all risk indicators to obtain the overall project risk index R:

6. The risk assessment method for tourism investment projects according to claim 1, wherein The specific steps for setting risk levels including extreme risk, severe risk, moderate risk, and mild risk are as follows: Let the extreme risk threshold be R 极度 , and the severe risk threshold be R 重度 , and the moderate risk threshold be R 中度 , then the risk level classification is expressed as: Extreme risk: R > R 极度 , Severe risk: R 重度 ≤ R < R 极度 , Moderate risk: R 中度 ≤ R < R 重度 , Mild risk: R < R 中度 .

7. The risk assessment method for tourism investment projects according to claim 1, wherein, The specific risk response strategies formulated according to the risk level include: Extreme risk response strategy: Immediately stop or adjust the project, seek external support, and formulate an emergency plan. Severe risk response strategy: Strengthen risk monitoring, optimize the risk management process, and take risk reduction measures. Moderate risk response strategy: Continuously monitor risk changes, formulate a risk mitigation plan, and strengthen internal communication. Mild risk response strategy: Conduct regular risk management, enhance risk awareness, and review risks regularly.

8. The risk early warning system for tourism investment projects corresponding to the risk assessment method for tourism investment projects according to claims 1-7, characterized in that, Including: Risk indicator definition and data collection module: Responsible for defining the risk assessment indicators of tourism investment projects, including external risks, internal risks of the investment entity, and project engineering risks, and collecting data related to the risk indicators. Bayesian risk assessment model module: Responsible for constructing a risk assessment model based on Bayes' theorem, calculating the occurrence probability of each risk indicator, and evaluating its impact on the overall project risk. Overall project risk assessment module: Responsible for comprehensively evaluating the posterior probabilities of each risk indicator and calculating the overall risk level of the project. Risk level comparison and decision-making module: Responsible for comparing the calculated overall risk level of the project with the preset risk level threshold to determine the current project risk level. Risk early warning and response mechanism module: responsible for triggering the corresponding risk early warning mechanism when the project risk level reaches or exceeds the set warning threshold, and formulating corresponding coping strategies according to different risk levels.

Images